Aiming at the problems of slow response and poor robustness of electric power steering system, the hardware structure of electric power steering system is designed, and a fuzzy control algorithm is proposed. The membership function of the fuzzy control algorithm is represented by Icon method, and the fuzzy theory set is planned.
Finally, the control algorithm is implemented by matlap. The simulation and validation show that the electric power steering system runs well and achieves the expected goal, which indicates that the design of the controller is successful. Compared with the traditional hydraulic system, the electric power steering system can reduce the driver’s fatigue strength and improve the safety and smoothness of driving. Compared with the traditional hydraulic system, the electric power steering system has the following advantages: it reduces the complicated layout of the hydraulic system, does not exist the leakage problem of hydraulic oil, and can effectively improve the response accuracy of the steering system, and has relative faults. Less, thermostatic element so it has gradually been widely used.
Domestic research on electric power steering system for automobiles has also achieved a lot of research results. Literature [12] studies the electric power system from the hardware structure, and achieves good results. Literature [35] analyzed and demonstrated the electric power steering system by software simulation. Literature [68] optimizes and designs the electric power steering system based on software control method, but the above control method has poor robustness, difficulty in implementation, high design cost and poor economy.
Aiming at the above problems, this paper optimizes and controls the control method of electric power steering system by using fuzzy control method, and designs the electronic hardware structure of the system. From Figure 1, it can be seen that the structure of the electric power steering device for automobiles is mainly as follows: rack and pinion steering gear, steering axle and steering column, torque sensor, motor and motor controller, and control computer ECU.
The working principle is as follows: During the steering process, the driver senses the steering angle and the steering moment by the torque sensor, and transmits this signal to ECU through LIN bus. The ECU obtains the driving speed of the vehicle through CAN bus. The computer judges the steering system according to the driving speed and the torque signal of the vehicle, and outputs a control system. The signal is made to the driving motor amplifier, and the electric amplifier amplifies the driving signal to drive the motor to rotate the corresponding angle. The motor rotates through the deceleration mechanism to drive the steering shaft to rotate, thus realizing the steering assistance. The system also realizes closed-loop control. The motor rotation is monitored by a rotation sensor in real time, and the motor rotation is fed back to the control computer. The computer judges the motor rotation according to the signal and realizes closed-loop control.
Fuzzy control is a control theory based on linguistic rules and fuzzy reasoning in modern control theory. It is an important branch of intelligent control. Because the steering dynamics of drivers in electric power steering system are not easy to grasp, it is difficult to express by qualitative mathematical model. However, from the qualitative understanding of steering process of automobile electric power steering system, it is easier to establish language control rules. Moreover, due to the start of control algorithm and system design method of electric power steering model.
Points and control objectives are different, which can easily lead to big differences. However, the fuzzy control algorithm can easily find a compromise method by making use of the fuzzy connection between the control laws of electric power steering, so that the control effect is better than that of the conventional controller. In addition, because the fuzzy control is designed based on heuristic knowledge and language decision rules, it can simulate the driver’s steering in the process of electric power steering. The process and method can improve the adaptability of the electric power steering control system, and make the system have certain predictability and intelligent learning ability. Secondly, the robustness of the fuzzy control system is stronger. The influence of the anti-interference ability and the change of external parameters on the control effect is greatly weakened. It is very suitable for the non-linear, time-varying and time-delay systems. Control [9], so this paper uses the fuzzy control strategy.
When the driver steers, the input of the controller of the electric power steering system is the torque signal from the torque sensor and the speed signal from the CAN bus. The control object is the drive motor of the electric power steering system. In the design of the controller, the error range of the torque signal is [4,4], the corresponding fuzzy universe is [4,4], quantization, seven levels, and the rest are boundary values, such as the toque signal is E, that is, [4,3,2,2,3,4], the fuzzy subset is {PB (positive), PS (positive), Z (zero), NS (negative), NB (negative)}. The membership function of the input can be expressed by pictures. The membership function of electric power steering motor can be referred to in reference [10]. In Figure 4, the X coordinate is the speed signal, the Y coordinate is the torque signal and the Z coordinate is the control signal of the electric power steering system. Next, the actual vehicle test is carried out. Firstly, the designed controller is loaded into the domestic Charley A refitted vehicle, and the speed signal of the dashboard is connected to the input interface of the electric power steering system through CAN bus. The power supply of the system is provided by the normal fire wire, and the negative pole is put on the iron to start the car. At the beginning, the driver controls the steering wheel to steer at a speed of 30Km/h, records and tests the driver’s sensation, then advances at a speed of 5km/h, rotates the steering wheel to record the driver’s sensation, and finally drives at a speed of 100km/h, and rotates the steering wheel to record the driver’s sensation. Three tests show that the electric power steering system can significantly reduce driving. Driver’s maneuvering strength and long driving time can reduce the driver’s labor intensity, reduce the steering wheel speed, especially reduce the steering force when parking and steering, and the return moment is large, which verifies the success of the electric power steering system.
Based on the design of the hardware structure of the electric power steering system, the hardware structure is optimized and simulated by using the method of fuzzy control strategy.
The results show that the system runs well, the system has high responsiveness, bigger return moment, smaller abnormal noise and obvious assist effect, which has played a good design effect.